OpenCV之霍夫变换

概述

OpenCV中的霍夫变换

霍夫变换原理

 

 

标准霍夫变换: HoughLines()函数

 

例程 

#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/video.hpp>
 
using namespace cv;
using namespace std;


int main(int argc, char** argv)
{
	//1.导入原始图和Mat变量定义
	Mat srcImage = imread("700levi.jpg");
	Mat midImage, dstImage;

	//2.进行边缘检测和转化为灰度图
	Canny(srcImage, midImage, 50, 200, 3);
	cvtColor(midImage, dstImage, COLOR_GRAY2BGR);

	//3.进行霍夫线转换
	vector<Vec2f> lines;//定义一个矢量结构lines用于存放得到的线段矢量集合
	HoughLines(midImage, lines, 1, CV_PI / 180, 150, 0, 0);

	//4.依次在图中绘制出每条线段
	for (size_t i = 0; i < lines.size(); i++)
	{
		float rho = lines[i][0], theta = lines[i][1];
		Point pt1, pt2;
		double a = cos(theta), b = sin(theta);
		double x0 = a * rho, y0 = b * rho;
		pt1.x = cvRound(x0 + 1000 * (-b));
		pt1.y = cvRound(y0 + 1000 * (a));
		pt2.x = cvRound(x0 - 1000 * (-b));
		pt2.y = cvRound(y0 - 1000 * (a));
		line(dstImage, pt1, pt2, Scalar(55, 100, 195), 1, LINE_AA);
	}

	//5. 显示原始图
	imshow("原始图", srcImage);

	//6. 边缘检测后的图
	imshow("边缘检测图", midImage);

	//7. 显示效果图
	imshow("效果图", dstImage);
	waitKey(0);
	return 0;
}

效果

累计概率霍夫变换:HoughLineP()函数

 

 例程

#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/video.hpp>
 
using namespace cv;
using namespace std;


int main(int argc, char** argv)
{
	//1.导入原始图和Mat变量定义
	Mat srcImage = imread("700levi.jpg");
	Mat midImage, dstImage;

	//2.进行边缘检测和转化为灰度图
	Canny(srcImage, midImage, 50, 200, 3);
	cvtColor(midImage, dstImage, COLOR_GRAY2BGR);

	//3.进行霍夫线转换
	vector<Vec4i> lines;//定义一个矢量结构lines用于存放得到的线段矢量集合
	HoughLinesP(midImage, lines, 1, CV_PI / 180, 80, 50, 10);

	//4.依次在图中绘制出每条线段
	for (size_t i = 0; i < lines.size(); i++)
	{
		Vec4i l = lines[i];
		line(dstImage, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(186, 88, 255), 1, LINE_AA);
	}

	//5. 显示原始图
	imshow("原始图", srcImage);

	//6. 边缘检测后的图
	imshow("边缘检测图", midImage);

	//7. 显示效果图
	imshow("效果图", dstImage);
	waitKey(0);
	return 0;
}

效果

PS: 效果稀碎, 可能需要调参

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转载自blog.csdn.net/sono_io/article/details/125375266